Hostname: page-component-7b9c58cd5d-dkgms Total loading time: 0 Render date: 2025-03-15T14:08:43.730Z Has data issue: false hasContentIssue false
  • English
  • Français

Harmonizing Data for Collaborative Research on Aging: Why Should We Foster Such an Agenda?

Published online by Cambridge University Press:  29 February 2012

Isabel Fortier ,
Dany Doiron ,
Christina Wolfson  and
Parminder Raina
Isabel Fortier*
Affiliation:
Research Institute of the McGill University Health Centre Public Population Project in Genomics
Dany Doiron
Affiliation:
Public Population Project in Genomics
Christina Wolfson
Affiliation:
McGill University
Parminder Raina
Affiliation:
McMaster University
*
*Correspondence and requests for offprints should be sent to: / La correspondance et les demandes de tirés-à-part doivent être adressées à: Isabel Fortier, Ph.D. Research Institute – McGill University Health Centre Allan Memorial Institute 1025 Pine Avenue West Room P2.028 Montreal, QC H3A 1A1 (isabel.fortier@mail.mcgill.ca)
Get access Rights & Permissions [Opens in a new window]

Abstract

An abstract is not available for this content so a preview has been provided. Please use the Get access link above for information on how to access this content.
Image of the first page of this content. For PDF version, please use the ‘Save PDF’ preceeding this image.'
Type
Canadian Institutes of Health Research–Institute of Aging: Profile
Information
Canadian Journal on Aging / La Revue canadienne du vieillissement , Volume 31 , Issue 1 , March 2012 , pp. 95 - 99
Copyright
Copyright © Canadian Association on Gerontology 2012

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Anstey, K.J., Byles, J.E., Luszcz, M.A., Mitchell, P., Steel, D., Booth, H., et al. . (2010). Cohort Profile: The Dynamic Analyses to Optimize Ageing (DYNOPTA) Project. International Journal of Epidemiology, 39(1), 44–51.Google Scholar
Borugian, M.J., Robson, P., Fortier, I., Parker, L., McLaughlin, J., Knoppers, B.M., et al. . (2010). The Canadian Partnership for Tomorrow project: Building a pan-Canadian research platform for disease prevention. CMAJ: Canadian Medical Association Journal [journal de l’Association medicale canadienne], 182(11), 1197–1201.Google Scholar
Cardis, E., Richardson, L., Deltour, I., Armstrong, B., Feychting, M., Johansen, C., et al. . (2007). The INTERPHONE study: Design, epidemiological methods, and description of the study population. European Journal of Epidemiology, 22(9), 647–664.Google Scholar
Cook, D.G., Shaper, A.G., & MacFarlane, P.W. (1989). Using the WHO (Rose) angina questionnaire in cardiovascular epidemiology. International Journal of Epidemiology, 18(3), 607–613.Google Scholar
Cooper, R., Hardy, R., Aihie Sayer, A., Ben-Shlomo, Y., Birnie, K., Cooper, C., et al. . (2011). Age and gender differences in physical capability levels from mid-life onwards: The harmonisation and meta-analysis of data from eight UK cohort studies. [doi:10.1371/journal.pone.0027899]. PLoS ONE, 6(11), e27899.Google Scholar
Craig, C.L., Marshall, A.L., Sjostrom, M., Bauman, A.E., Booth, M.L., Ainsworth, B.E., et al. . (2003). International physical activity questionnaire: 12-country reliability and validity. Medicine and Science in Sports and Exercise, 35(8), 1381–1395.Google Scholar
Esteve, A., & Sobek, M. (2003). Challenges and methods of international census harmonization. Historical Methods: A Journal of Quantitative and Interdisciplinary History, 36(2), 66–79.Google Scholar
Fortier, I., Burton, P.R., Robson, P.J., Ferretti, V., Little, J., L’Heureux, F., et al. . (2010). Quality, quantity and harmony: The DataSHaPER approach to integrating data across bioclinical studies. International Journal of Epidemiology, 39(5), 1383–1393.Google Scholar
Granda, P., & Blasczyk, E. (2010). Data harmonization guidelines for best practice in cross-cultural surveys. Ann Arbor, MI: Survey Research Center, Institute for Social Research, University of Michigan.Google Scholar
Hamilton, C.M., Strader, L.C., Pratt, J.G., Maiese, D., Hendershot, T., Kwok, R.K., et al. . (2011). The PhenX toolkit: Get the most from your measures. American Journal of Epidemiology, 174(3), 253–260.Google Scholar
Holman, C.D., Bass, A.J., Rosman, D.L., Smith, M.B., Semmens, J.B., Glasson, E.J., et al. . (2008). A decade of data linkage in Western Australia: Strategic design, applications and benefits of the WA data linkage system. Australian Health Review, 32(4), 766–777.Google Scholar
Lee, J. (2007). Harmonization of aging surveys and cross-national studies of aging executive summary. Meeting Report, Chiang Mai, Thailand. National Institute on Aging, Behavioral and Social Research Program.Google Scholar
National Research Council. (2001). Preparing for an aging world: The case for cross-national research. Washington, DC.Google Scholar
Raina, P.S., Wolfson, C., Kirkland, S.A., Griffith, L.E., Oremus, M., Patterson, C., et al. . (2009). The Canadian Longitudinal Study on Aging (CLSA). Canadian Journal on Aging [Revue canadienne du vieillissement], 28(Special Issue 03), 221–229.Google Scholar
Riboli, E., & Kaaks, R. (1997). The EPIC Project: Rationale and study design. European Prospective Investigation into Cancer and Nutrition. International Journal of Epidemiology, 26(Suppl. 1), S6.Google Scholar